Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 25 von 96

Details

Autor(en) / Beteiligte
Titel
Automated analysis of neuronal morphology, synapse number and synaptic recruitment
Ist Teil von
  • Journal of neuroscience methods, 2011-02, Vol.195 (2), p.185-193
Ort / Verlag
Netherlands: Elsevier B.V
Erscheinungsjahr
2011
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • [Display omitted] ▶ SynD reliably analyzes dendrite length and synapse number. ▶ SynD automatically quantifies dendritic branching and synaptic localization. ▶ SynD measures synapse intensity and synaptic localization of proteins. ▶ Image analysis in SynD is time-efficient. ▶ SynD is not limited to synapse detection in cultured neurons. The shape, structure and connectivity of nerve cells are important aspects of neuronal function. Genetic and epigenetic factors that alter neuronal morphology or synaptic localization of pre- and post-synaptic proteins contribute significantly to neuronal output and may underlie clinical states. To assess the impact of individual genes and disease-causing mutations on neuronal morphology, reliable methods are needed. Unfortunately, manual analysis of immuno-fluorescence images of neurons to quantify neuronal shape and synapse number, size and distribution is labor-intensive, time-consuming and subject to human bias and error. We have developed an automated image analysis routine using steerable filters and deconvolutions to automatically analyze dendrite and synapse characteristics in immuno-fluorescence images. Our approach reports dendrite morphology, synapse size and number but also synaptic vesicle density and synaptic accumulation of proteins as a function of distance from the soma as consistent as expert observers while reducing analysis time considerably. In addition, the routine can be used to detect and quantify a wide range of neuronal organelles and is capable of batch analysis of a large number of images enabling high-throughput analysis.

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX